4.7 Article

Decomposition of energy intensity in Chinese industries using an extended LMDI method of production element endowment

Journal

ENERGY
Volume 221, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.119846

Keywords

Extended LMDI; Energy intensity; Chinese industry; Production element endowment; Development mode; R& D expenditure

Funding

  1. National Social Science Foundation of China [16ZDA044]

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This study decomposes the impacting factors of production element endowment on energy intensity in China's industries from 2000 to 2015, finding that labor-technology ratio and energy-capital ratio are the two main contributors to the decline in energy intensity. Meanwhile, capital-labor ratio, investment intensity, and R&D intensity play roles in increasing energy intensity in Chinese industry.
The purpose of this paper is to decompose the impacting factors of production element endowment (PEE) on energy intensity in China's industries in 2000-2015. This is vital for China's policy-making in terms of the development of low-energy-consumption (LEC) industries under relatively rapid industri-alization and urbanization. This study contributes to the comprehensive investigation of PEE's impact on energy intensity (EI), which can bridge the existing literature gap. A PEE extended logarithmic mean Divisia index (LMDI) method was developed to decompose the changes in the Chinese industrial EI into three PEE, two intensity, and two structure factors. These driving factors include the energy-capital ratio (EK), capital-labor ratio (KL), labor-technology ratio (LT), R&D intensity (RI), investment intensity (II), energy mix (ES), and share of provincial industrial output (OS). The results demonstrated the following. (1) Overall, the effects of LT and EK are the two leading con-tributors to the decline in EI in Chinese industry. Moreover, OS exerted a negative effect on EI, and ES showed a marginal negative effect on EI. KL, II, and RI played roles in the increase in Chinese industrial EI. (2) In terms of the cumulative effects at the provincial level, LT and KL had the largest curbing and stimulating effect on the EI of all provinces, respectively. EK, II, RI, and OS had positive or negative effects on EI in all provinces with some fluctuations. Among all factors, the ES effect was the weakest and demonstrated mixed results in different provinces. (3) In the eastern, central, and western regions, LT, EK, and OS decreased Chinese industrial EI. KL, II, and RI were the three major contributors to the improvement in EI. Finally, the policy recommendations for EI reduction in Chinese industry are pre-sented on the basis of the empirical results.

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